Writing a radiology report can be time-consuming and tedious for experienced radiologists, and error-prone for un-experienced radiologists [1]}. Similar to image paragraph generation, most existing works [1]}, [3]}, [4]} attempt to adopt a HRNN to automatically generate a fluent report. However, due to the serious data deviation, these models are poor at finding visual groundings and are biased towards generating plausible but general reports without prominent abnormal narratives [5]}, [6]}, [4]}, [8]}.
